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IS480 Team wiki: 2012T1 M.O.O.T/Project Management

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Project Schedule Schedule & Bug Metrics Gender Recognition Metrics Risk Management Minutes Repository

Post-Acceptance Project Schedule

Planned Schedule Summary

This is the latest schedule amended prior to the beginning of iteration 3. After numerous discussions, we have been informed that CMA would really like to have photo-taking feature. Our primary research of measurement collection in iteration 1 has also shown us that it is not possible to determine gender based on Waist-Hip ratio as waist is not detected by Kinect. The highlight of the schedule amendment is hence the changes of interactive features to photo taking feature and gender recognition based on 4 parameters: height, shoulder length, whether shopper is holding on to a handbag, and whether shopper is wearing long skirt. The focus will be on gender recognition based on neural network until midterm, followed by development of photo taking feature post midterm.


WithPhotoTakingScheduleSummary.png


Access previous planned schedules to view earlier planned schedules prior to firming up of client requirements and primary research on differences between male and female.

Weekly Progress

Week Date Scheduled Features Completed Features Pending Features/Remarks
1 17/08/12 – 24/08/12
  • Explore Classifier Algorithm (CA)
  • Measurement collection
  • Theoretical understanding of Neural Network (NN) and its classification feature
  • Measurement collection
N.A.
2 25/08/12 – 31/08/12
  • Analysis of measurement collection
  • Gender differences trend establishment
  • Gender recognition based on Waist-to-Hip Ratio (WHR)
  • NN classification
  • Analysis of physical measurement collection classification feature
  • Gender differences trend establishment based on physical measurement analysis & secondary research
  • Measurement of height based on image captured by Kinect
  • Found that waist cannot be detected by Kinect, hence dropping WHR
  • Difficulties encountered in implementing NN classification
3 01/09/12 – 08/09/12
  • NN classification & scoring system
  • Parameters expansion: neck & shoulder width
  • Passing of height and shoulder width captured by Kinect to NN
  • NN classification based on height and shoulder width
  • Decided to include parameters hasBag & hasSkirt instead of neck width in the upcoming week
4 09/09/12 – 16/09/12
  • Gender recognition based on complete set of inputs
  • Capturing shopper’s outline
  • Countdown timer
  • Gender recognition based on height & shoulder width
  • hasBag & hasSkirt displayed for consideration
  • Countdown timer
  • Refining of shopper's outline
  • hasSkirt, hasBag parameters to be improved and integrated with passing in of parameters through Kinect
5 17/09/12 – 23/09/12
  • Capturing of photo
  • Backward propagation
  • Saving learning state
  • Integration of photo taking with gender recognition
  • Capturing of photo
  • Backward propagation
  • Integration of photo taking with gender recognition
  • Saving learning state is pushed back to Iteration 6
6 24/09/12 – 29/09/12
  • Microsoft Tag
  • Advertisement Management System page
  • Refining overlaying of augmented background
  • Integration of Microsoft Tag into photos
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking
  • Microsoft Tag
  • Advertisement Management System page
  • Refining overlaying of augmented background
  • Integration of Microsoft Tag into photos
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking

Behavioural parameters were not very accurate

7 01/10/12 – 06/10/12
  • Using real figures instead of Kinect figures
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking
  • Integration of Microsoft Tag, gender recognition, and photo taking
  • Using real figures instead of Kinect figures
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking
  • Integration of Microsoft Tag, gender recognition, and photo taking
N.A.
8 08/10/12 – 12/10/12
  • Scene transition
  • Display shopper's silhouette
  • Make callout bubble dynamic
  • Code clean up
  • Scene transition
  • Display shopper's silhouette
  • Integration of outline-photo-taking-displaying photo with tag
  • Make callout bubble dynamic
9 15/10/12 – 19/10/12
  • Choosing of door
  • Unsupervised learning
  • Make callout bubble dynamic
  • Stick man approaching chosen door
  • Debugging of bug: crashing in the wild
  • Choosing of door
  • Auto-rescale callout bubble
  • Stick man approaching chosen door
  • Recording of learning response to database
  • Debugging of head-depth bug causing crash in wild environment
  • Callout bubble position needs to be relative to user's
  • Integration of unsupervised learning to AlterSense
10 22/10/12 – 26/10/12
  • Debug to enable reverting to scene 0
  • Relating door scene image with photo taking scene
  • Integration of unsupervised learning to AlterSense
  • Callout bubble to follow (relative to)user's position
  • Activation of training upon detection of dropping accuracy
  • Relating door scene image with photo taking scene
  • Callout bubble to follow (relative to)user's position
  • Integration of unsupervised learning to AlterSense
  • Debug to enable reverting to scene 0
  • Unsupervised learning to be modified to be less obvious
  • Activation of training upon detection of dropping accuracy
11 29/10/12 – 02/11/12
  • Modified unsupervised learning (Scene 3)
  • Gender-targeted content insertion into AMS
  • Modified display of tag for enhanced user experience
  • Instructional callouts to choose door and scan tag
  • Activation of training upon detection of dropping accuracy
  • Thorough integration for User Testing 2

Finals Wiki

M.O.O.T Final Wiki
1. Project Progress Summary
1.1. Project Highlights
1.2. Project Challenges
1.3. Project Achievements
2. Project Management
2.1. Project Schedule
2.2. Project Metrics
2.3. Technical Complexity
3. Quality of Product
3.1. Project Deliverable
3.2. Quality
3.3. Deployment
3.4. Testing
4. Reflection
4.1. Team Reflection
4.2. Individual Reflection
4.3. Sponsor Comment

Midterm Wiki

M.O.O.T Midterm Wiki
1. Project Progress Summary
1.1. Project Highlights
2. Project Management
2.1. Project Status
2.2. Project Schedule
2.3. Project Metrics
2.4. Project Risks
2.5. Technical Complexity
3. Quality of Product
3.1. Intermediate Deliverables
3.2. Deployment
3.3. Testing
4. Reflection
4.1. Team Reflection
4.2. Individual Reflection

Pre-Acceptance

MOOTschedule.jpg